class_docstr: Segment info augmented with Sound metadata.
      
code: def from_dict(cls, dictionary: dict, fields_required: bool = False):
      _dictionary: tp.Dict[str, tp.Any] = {}
  
      # allow a subset of attributes to not be loaded from the dictionary
      # these attributes may be populated later
      post_init_attributes = ["self_wav"]
  
      for _field in fields(cls):
          if _field.name in post_init_attributes:
              continue
          elif _field.name not in dictionary:
              if fields_required:
                  raise KeyError(
                      f"Unexpected missing key: {_field.name}"
                  )
          else:
              preprocess_func: tp.Optional[
                  tp.Callable
              ] = cls.attribute_getter(_field.name)
              value = dictionary[_field.name]
              if preprocess_func:
                  value = preprocess_func(value)
              _dictionary[_field.name] = value
      return cls(**_dictionary)
  
imports: from dataclasses import dataclass, fields, replace
  import json
  from pathlib import Path
  import random
  import typing
  import numpy
  import torch
  from .info_audio_dataset import InfoAudioDataset, get_keyword_or_keyword_list
  from ..modules.conditioners import ConditioningAttributes, SegmentWithAttributes, WavCondition
label_desc: Use image node_id 4 for calling the SoundInfo obj's underlying member method code with example usage: obj.from_dict(cls, dictionary, fields_required) and returns: cls